Results for “gender-detection”

Scores genetic compatibility between all male-female pairings in a Genomebook generation, ranking optimal mating pairs based on heterozygosity, trait complementarity, and disease risk.

Trains, evaluates, exports, and runs inference for Visual ChangeNet models used in AOI defect detection, comparing image pairs for PASS/NO_PASS classification or change-segmentation masks.

Trains, evaluates, exports, and runs inference for person re-identification models using TAO, learning discriminative embeddings for cross-camera matching.

Trains, evaluates, exports, prunes, quantizes, retrains, and runs inference for OCDNet scene text detection models using TAO, detecting arbitrary-oriented text regions in natural images.

Detects all languages used on a webpage — both declared (html@lang, hreflang, nested lang=, meta content-language) and actually present in the body text using Google CLD3 WASM. Reconciles the two signal sets and flags mismatches for i18n audits, hreflang validation, and multilingual content verification.

Trains and fine-tunes vision models for object detection, image classification, and segmentation using Hugging Face Transformers on cloud GPUs, with automatic dataset validation and Hub persistence.

Trains, evaluates, exports, quantizes, and runs inference for a Grounding DINO model that detects objects described by text prompts without a fixed class vocabulary.

Train, evaluate, export, and run inference for pose classification models using ST-GCN on skeleton keypoint sequences.

Engineering privacy and data governance: PII detection, data flow mapping, consent patterns, GDPR/CCPA-compliant implementation, DPIA. Use when privacy-by-design is needed.

Evaluates text-to-image models on spatial relationship accuracy using the VISOR metric, separating object detection from spatial correctness to reveal biases like object priority and merging.

Detects DNS tunneling by computing Shannon entropy of DNS query names, analyzing query length distributions, inspecting TXT record payloads, and identifying high subdomain cardinality using scapy for packet capture analysis.

Detects and ranks trending market themes by analyzing cross-sector momentum, volume, and breadth signals with lifecycle maturity assessment.

Research Guardian - Ethics Advisory & Bias Detection across all research stages Enhanced VS 3-Phase process: Surface-level screening, deep contextual analysis, constructive recommendations Use when: reviewing research ethics, checking for bias, assessing trustworthiness, QRP screening Triggers: ethics review, IRB, bias detection, QRP, trustworthiness, research integrity, p-hacking, HARKing

Diagnose monogenic and syndromic obesity in children and adolescents using a structured step-by-step algorithm. Use this skill whenever a clinician suspects a genetic cause of obesity, asks about leptin deficiency, MC4R mutation, POMC deficiency, PCSK1 deficiency, leptin receptor deficiency, Bardet-Biedl syndrome, Prader-Willi syndrome, Alström syndrome, or any case of early-onset severe obesity with hyperphagia. Also trigger for questions about targeted pharmacotherapy including setmelanotide or metreleptin, or when to order a genomic obesity panel. Cross-references the NHS Genomic Test Finder skill to surface the relevant R-code once a diagnosis is reached.

Performs differential expression analysis on bulk RNA-seq or pseudo-bulk count matrices with QC, PCA, and contrast testing.

Extracts a public-safe brand and offer profile for paid advertising from an authorized website and operator input.

Detect splice donor and acceptor sites in DNA sequences using the Genomic Intelligence G0 BigBird transformer, via the hosted /v1/tasks/splice/predict API. Returns per-position site probabilities and called sites.

Casting personas: rapid generation from diverse inputs, registry-based persistence and lifecycle, data-driven evolution, inter-agent sync. Not for UI walkthroughs (Echo) or user research (Field).

Graph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, GAT, SchNet), 40+ datasets, for PyTorch-based ML on molecules, proteins, and biomedical graphs.

Cardinality and model family jointly determine the encoding.

Performance regression detection using the browse daemon. Establishes baselines for page load times, Core Web Vitals, and resource sizes. Compares before/after on every PR. Tracks performance trends over time. Use when: "performance", "benchmark", "page speed", "lighthouse", "web vitals", "bundle size", "load time". (gstack) Voice triggers (speech-to-text aliases): "speed test", "check performance".

Evaluates the correlation between automatic text generation scores and human quality ratings, including robustness to domain and quality drift, using metrics like Kendall's Tau and Pearson correlation.

Open-Vocabulary Object Detection Using Captions

Generate images with Google Nano Banana 2 (Gemini-family flash-tier text-to-image) on RunComfy — bundled with the model's documented prompting patterns so the skill gets sharper output than naive prompting against the same model. Documents Nano Banana 2's strengths (rapid iteration, in-image typography rendering, predictable framing, optional web-grounded context), the resolution-tier pricing, the safety-tolerance dial, and when to route to Nano Banana Pro / GPT Image 2 / Flux 2 / Seedream instead. Calls `runcomfy run google/nano-banana-2/text-to-image` through the local RunComfy CLI. Triggers on "nano banana", "nano-banana-2", "nano banana 2", "google image gen", "gemini image", or any explicit ask to generate with this model.

Detect poisoned training data and backdoored models across the ML pipeline using statistical analysis, activation clustering, and spectral signatures.

Detect abuse of legitimate Windows binaries (LOLBins) like certutil, regsvr32, mshta, and rundll32 using process telemetry, Sigma rules, and parent-child process analysis.

Systematically fuzz web applications for hidden content and input validation vulnerabilities across directories, files, parameters, and authentication bypasses.

DeepEval — LLM evaluation framework, RAG metrics, hallucination detection, red-teaming, CI/CD integration

Score any piece of writing for AI-generation tells and produce a weighted 0-100 scorecard with flagged evidence and ranked fixes. Use this skill whenever the user asks "does this sound AI-written", "run this through the AI detector", "score this writing", "check this for AI tells", "would this pass as human", "humanize check", or wants any article, blog post, email, or copy audited for AI patterns before publishing. Also use it when the user pastes or points to text and asks how it reads, whether it's too "ChatGPT-ish", or wants a QA pass on generated content. Works on pasted text, files, and URLs.

画像を理解（被写体・テキストOCR・構図・色・UI構造の分析）し、結果を構造化して返すスキル。CC CLI は GLM-5.3 等の vision 非対応モデルで稼働中のため画像を直接視認できず、主ルート Gemini 2.5 Flash（scripts/api/gemini_vision.py・無料枠）と副ルート 4_5v MCP（analyze_image・Readが返すCDN URL）の2経路で分析し、CCは結果の構造化・比較・保存に専任する。 ユーザーが「画像見て」「この画像何が写ってる」「画像比較して」「スクショ見て」「画像分析して」「画像理解」「vision-analyze」と言った時、または /vision-analyze を呼んだ時にトリガー。 ※画像生成（image generation）は対象外（make-song / video-prompt-spec / demo-site-sales参照）。ピクセル修正（花鈿除去等）は remove-huadian の役割。楽曲分析は analyze-song / reverse-engineer-song。

Guardian of V.A.I.R.E. quality standards (Value/Agency/Identity/Resilience/Echo). Handles pre-release evaluation, scorecard assessment, and pass/fail determination. Use when UX quality gates are needed. Does not write code.

Generate Image (gemini / openai backends)

Analyze AWS GuardDuty findings, detectors, suppression rules, and member accounts with parallel execution and anti-hallucination guardrails.

HNSW vector search for pattern similarity retrieval and knowledge graph maintenance with PageRank scoring, community detection, and 3-tier memory management.

Validates the Emotional Attitude Score (EAS) metric by measuring its consistency with human judgment on word-level sentiment polarity, using the AmbGIMT dataset and pairwise score comparisons.